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The Main Technologies behind Chatbots

Jun 14, 2017

The Main Technologies behind Chatbots

No more repetitive tasks!

How many times have you said to yourself: “this process could cost a lot less if it was automated” or “I’m tired of always answering the same questions” or even “I would like it if someone would remind me of this”?
Actually, we are increasingly demanded to multi-task and the need for solving these demands is already a reality.
What if we could solve this overwhelming demand with assistants; even better, with technology?
This was very complex and very costly in the recent past, but thanks to chatbots a large amount of these problems is being solved in a fast, intelligent and automated way.

Chatbots – What are they?

Basically, chatbots are computer programs (software) developed to do tasks while simulating human behavior in a conversation. They can automate processes, answer questions, consult on a specific subject and integrate itself in another system. The limit is restricted only by the need.

One of the main attractions of chatbots is the capability of verbal interaction with users to speed-up repetitive process on an external system. Think about the following situation: a customer wants to search by a specific item in an e-commerce page, he will need to navigate to the page, find the product, click on the description tab, and maybe he will find the information that he needs.

But what if instead of doing all this process he could just ask an attendant for the needed information? Faster right? And if right before he gets this information the customer decides to add the product to their cart? What will be the best experience, be redirected to a new page or simply ask for it?

This ease is not just for business. There are already chatbots to help people identifying diseases through symptoms, chatbots to manage calendars and appointments, to help on car rentals, etcetera. All this by a computer or smartphone and speech!

Technology vs. human behavior

Recently I had the chance to work with those technologies in a deeper way and I’ve noticed that one of the questions someone who wants to start a chatbot project usually asks is: how to predict the way users’ will communicate with the system. Every single user is a new user and doesn’t always start a conversation with “hi” or “hello” and won’t end a conversation with “bye” or “thank you” every time. The user can simply say “see you later” or he can even be more relaxed and say “bye bro”. So how can we deal with this challenge of predicting the human behavior assertively?

There are technologies nowadays that give chatbots the capability to learn new communication patterns according to their use. This kind of “self-upgrade” is called Machine-Learning, and the act of communicate adapting to a user’s behavior is called Natural Language. That is basically the language that humans are used to.

Real cases

I’ve been involved in some of the projects developed by Actminds and I’ve had the opportunity to experience a number of similar situations, such as:

On one of the projects we needed to “generate an access token to the internal network”, but we couldn’t force the users to use terms like “Token Wi-Fi” or “Wi-Fi Password” or “Access to Wi-Fi”.

To solve this kind of problem we adopted a machine-learning based solution, because this way it’s not necessary to think about all the possible interactions but only with the most common ones.

Another chatbot project had the objective of identify possible diseases based on the users described symptoms. For example: “I’m feeling a stomach ache” or “my belly hurts”. On many of these cases these users wanted to express the same symptom but with different words.

The chatbot starts to recognize new communication patterns to express specific intentions and with time and training it will be able to consider “bye bro” as a way of saying goodbye and recognize “Wi-Fi password” and “token wi-fi” as meaning exactly the same thing for the user.

Surely a market trend

Today chatbots already exist capable of voice communication, integrating themselves to Cortana, as an example of e multi language chatbot. The great advantage of a chatbot that communicates over an IVR is its capability of changing the context of the conversation and adapt itself to the user, making the experience more natural.

And is that practicality on the user X system interaction and his versatility that turns chatbots so popular and a trend on the technology market.

A lot of enterprises are betting on this kind of technology to attend faster and more efficiently their demands on diverse layers of their business.

So, prepare yourself. The chatbots are coming, stronger, smarter and more efficient to empower businesses, customers and users alike!